Studies from Department of Computer Sciences and Engineering Provide New Data on Schizophrenia (Unveiling Psychotic Disorder Patterns: a Deep Learning Model Analysing Motor Activity Time-series Data With Explainable Ai).

A recent study conducted by the Department of Computer Sciences and Engineering in New Delhi, India, explores the potential of deep learning models in revolutionizing healthcare, specifically in the field of mental health. The study focuses on the use of motor activity time-series data to analyze patterns of psychotic disorders, such as schizophrenia. The researchers developed a multi-branch deep learning architecture that effectively classified depressive and schizophrenic episodes from control subjects with an accuracy of 0.94. The study concludes that combining control samples from different datasets further increased the accuracy to 0.97 for depression and 0.98 for schizophrenia. [Extracted from the article]